Artificial intelligence systems aim to sniff out signs of COVID-19 outbreaks
The international alarm about the COVID-19 pandemic was sounded first not by a human, but by a computer. HealthMap, a website run by Boston Children’s Hospital, uses artificial intelligence (AI) to scan social media, news reports, internet search queries, and other information streams for signs of disease outbreaks. On 30 December 2019, the data-mining program spotted a news report of a new type of pneumonia in Wuhan, China. The one-line email bulletin noted that seven people were in critical condition and rated the urgency at three on a scale of five.
Humans weren’t far behind. Colleagues in Taiwan had already alerted Marjorie Pollack, a medical epidemiologist in New York City, to chatter on Weibo, a social media site in China, that reminded her of the 2003 outbreak of severe acute respiratory syndrome (SARS), which spread to dozens of countries and killed 774.
“It fit all of the been there, done that déjà vu for SARS,” Pollack says. Less than 1 hour after the HealthMap alert, she posted a more detailed notice to the Program for Monitoring Emerging Diseases, a list server with 85,000 subscribers for which she is a deputy editor.
But the early alarm from HeathMap underscores the potential of AI, or machine learning, to keep watch for contagion. As the COVID-19 pandemic continues to spread around the globe, AI researchers are teaming with tech companies to build automated tracking systems that will mine vast amounts of data, from social media and traditional news, for signs of new outbreaks. AI is no substitute for traditional public health monitoring, cautions Matthew Biggerstaff, an epidemiologist with the U.S. Centers for Disease Control and Prevention (CDC). “This should be viewed as one tool in the toolbox,” he says. But it can fulfill a need, says Elad Yom-Tov, a computer scientist with Microsoft who has worked with public health officials in the United Kingdom.
“There’s such a wealth of data, we will need some sort of tool to make sense of those data, and to me that tool is machine learning.”
Well before COVID-19 hit, CDC began an annual competition to most accurately predict the severity and spread of influenza across the United States.
Many of teams involved in the flu challenge have now pivoted to tracking COVID-19. They are applying AI in two ways. It can strive to spot the first signs of a new disease or outbreak, just as HealthMap did.
AI can also be used to assess the current state of an epidemic—so-called now-casting. The Carnegie Mellon teams aims to now-cast COVID-19 across the United States, using data collected through pop-up symptom surveys by Google and Facebook, Google search data, and other sources in order to predict local demand for intensive care beds and ventilators 4 weeks into the future. - Sciencemag.org
Humans weren’t far behind. Colleagues in Taiwan had already alerted Marjorie Pollack, a medical epidemiologist in New York City, to chatter on Weibo, a social media site in China, that reminded her of the 2003 outbreak of severe acute respiratory syndrome (SARS), which spread to dozens of countries and killed 774.
“It fit all of the been there, done that déjà vu for SARS,” Pollack says. Less than 1 hour after the HealthMap alert, she posted a more detailed notice to the Program for Monitoring Emerging Diseases, a list server with 85,000 subscribers for which she is a deputy editor.
But the early alarm from HeathMap underscores the potential of AI, or machine learning, to keep watch for contagion. As the COVID-19 pandemic continues to spread around the globe, AI researchers are teaming with tech companies to build automated tracking systems that will mine vast amounts of data, from social media and traditional news, for signs of new outbreaks. AI is no substitute for traditional public health monitoring, cautions Matthew Biggerstaff, an epidemiologist with the U.S. Centers for Disease Control and Prevention (CDC). “This should be viewed as one tool in the toolbox,” he says. But it can fulfill a need, says Elad Yom-Tov, a computer scientist with Microsoft who has worked with public health officials in the United Kingdom.
“There’s such a wealth of data, we will need some sort of tool to make sense of those data, and to me that tool is machine learning.”
Well before COVID-19 hit, CDC began an annual competition to most accurately predict the severity and spread of influenza across the United States.
Many of teams involved in the flu challenge have now pivoted to tracking COVID-19. They are applying AI in two ways. It can strive to spot the first signs of a new disease or outbreak, just as HealthMap did.
AI can also be used to assess the current state of an epidemic—so-called now-casting. The Carnegie Mellon teams aims to now-cast COVID-19 across the United States, using data collected through pop-up symptom surveys by Google and Facebook, Google search data, and other sources in order to predict local demand for intensive care beds and ventilators 4 weeks into the future. - Sciencemag.org
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